WO2020209923A2 - Systèmes et procédés de détection d'armes et de dispositifs destructifs sur la base d'un profil de champ électromagnétique - Google Patents

Systèmes et procédés de détection d'armes et de dispositifs destructifs sur la base d'un profil de champ électromagnétique Download PDF

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Publication number
WO2020209923A2
WO2020209923A2 PCT/US2020/015136 US2020015136W WO2020209923A2 WO 2020209923 A2 WO2020209923 A2 WO 2020209923A2 US 2020015136 W US2020015136 W US 2020015136W WO 2020209923 A2 WO2020209923 A2 WO 2020209923A2
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WIPO (PCT)
Prior art keywords
electromagnetic field
objects
computing device
predetermined
sensors
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PCT/US2020/015136
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English (en)
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WO2020209923A3 (fr
Inventor
Gregory Alton HOLIFIELD
Timothy Alton HOLIFIELD
Lawrence Edward STALLMAN
Pabio Jose PRADO
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Tesseract Sensors, LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by Tesseract Sensors, LLC filed Critical Tesseract Sensors, LLC
Priority to MX2021009010A priority Critical patent/MX2021009010A/es
Priority to BR112021014687-3A priority patent/BR112021014687A2/pt
Priority to AU2020271483A priority patent/AU2020271483A1/en
Priority to US17/419,334 priority patent/US20220082721A1/en
Priority to CA3127933A priority patent/CA3127933A1/fr
Priority to EP20788418.0A priority patent/EP3914940A2/fr
Priority to GB2112194.2A priority patent/GB2595192A/en
Publication of WO2020209923A2 publication Critical patent/WO2020209923A2/fr
Publication of WO2020209923A3 publication Critical patent/WO2020209923A3/fr
Priority to CONC2021/0011317A priority patent/CO2021011317A2/es

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/08—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices
    • G01V3/081—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices the magnetic field is produced by the objects or geological structures
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/08—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices
    • G01V3/10—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices using induction coils
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/64—Three-dimensional objects
    • G06V20/647—Three-dimensional objects by matching two-dimensional images to three-dimensional objects
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/61—Control of cameras or camera modules based on recognised objects

Definitions

  • the presently disclosed subject matter relates generally to security systems. Particularly, the presently disclosed subject matter relates to systems and methods for weapon and destructive device detection based on electromagnetic field profile.
  • FIG. 1 is a diagram of a system for weapon and destructive device detection based on electromagnetic field profile in accordance with embodiments of the present disclosure
  • FIG. 2 is a flowchart of an example method for detecting weapons and destructive devices based on electromagnetic field profiles in accordance with embodiments of the present disclosure
  • FIG. 3 is a graph showing a signal of a test magnet being rotated end- over-end to produce an oscillating signal at a distance of 9.2 m from two induction-coil sensors, along with the residual obtained by least squares subtraction of one sensor output from the other;
  • FIG. 4 is a graph that shows the signal from the same magnet being carried twice past the sensors at a brisk walking pace, with the distance at closest approach being 4.7 m;
  • FIGs. 5A and 5B illustrate a side perspective view and a side view, respectively, of an example solenoid coil with a high permeability core that may be used as a sensor in accordance with embodiments of the presently disclosed subject matter;
  • FIGs. 6-10 are different views of example configurations of weapon and destructive device detection system in accordance with embodiments of the present disclosure.
  • FIG. 11 is a diagram of an example configuration for entryway security in accordance with embodiments of the present disclosure.
  • FIG. 12 is a block diagram of an example system 1300 for implementing functionality described herein.
  • a system includes one or more sensors configured to detect an electromagnetic field of one or more objects and to output an electrical signal representative of the electromagnetic field.
  • the system also includes a computing device operably connected to the one or more sensors. Further, the computing device is configured to receive the electrical signal. The computing device is also configured to determine whether each of the one or more objects meets a predetermined electromagnetic field profile based on the electrical signal. Further, the computing device is configured to present a notification to a user in response to determining that one of the objects meet the predetermined electromagnetic field profile.
  • Articles“a” and“an” are used herein to refer to one or to more than one (i.e. at least one) of the grammatical object of the article.
  • “an element” means at least one element and can include more than one element.
  • “About” is used to provide flexibility to a numerical endpoint by providing that a given value may be“slightly above” or“slightly below” the endpoint without affecting the desired result.
  • a computing device may be implemented in programmable hardware devices such as processors, digital signal processors, central processing units, field programmable gate arrays, programmable array logic, programmable logic devices, cloud processing systems, or the like.
  • the computing devices may also be implemented in software for execution by various types of processors.
  • An identified device may include executable code and may, for instance, comprise one or more physical or logical blocks of computer instructions, which may, for instance, be organized as an object, procedure, function, or other construct. Nevertheless, the executable of an identified device need not be physically located together but may comprise disparate instructions stored in different locations which, when joined logically together, comprise the computing device and achieve the stated purpose of the computing device.
  • a computing device may be a server or other computer located within a retail environment and communicatively connected to other computing devices (e.g., POS equipment or computers) for managing accounting, purchase transactions, and other processes within the retail environment.
  • a computing device may be a mobile computing device such as, for example, but not limited to, a smart phone, a cell phone, a pager, a personal digital assistant (PDA), a mobile computer with a smart phone client, or the like.
  • PDA personal digital assistant
  • a computing device may be any type of wearable computer, such as a computer with a head-mounted display (HMD), or a smart watch or some other wearable smart device. Some of the computer sensing may be part of the fabric of the clothes the user is wearing.
  • HMD head-mounted display
  • a computing device can also include any type of conventional computer, for example, a laptop computer or a tablet computer.
  • a typical mobile computing device is a wireless data access-enabled device (e.g., an iPHONE ® smart phone, a BLACKBERRY ® smart phone, a NEXUS ONETM smart phone, an iPAD ® device, smart watch, or the like) that is capable of sending and receiving data in a wireless manner using protocols like the Internet Protocol, or IP, and the wireless application protocol, or WAP.
  • This allows users to access information via wireless devices, such as smart watches, smart phones, mobile phones, pagers, two-way radios, communicators, and the like.
  • Wireless data access is supported by many wireless networks, including, but not limited to, Bluetooth, Near Field Communication, CDPD, CDMA, GSM, PDC, PHS, TDMA, FLEX, ReFLEX, iDEN, TETRA, DECT, DataTAC, Mobitex, EDGE and other 2G, 3G, 4G, 5G, and LTE technologies, and it operates with many handheld device operating systems, such as PalmOS, EPOC, Windows CE, FLEXOS, OS/9, JavaOS, iOS and Android.
  • these devices use graphical displays and can access the Internet (or other communications network) on so-called mini- or micro-browsers, which are web browsers with small file sizes that can accommodate the reduced memory constraints of wireless networks.
  • the mobile device is a cellular telephone or smart phone or smart watch that operates over GPRS (General Packet Radio Services), which is a data technology for GSM networks or operates over Near Field Communication e.g. Bluetooth.
  • GPRS General Packet Radio Services
  • a given mobile device can communicate with another such device via many different types of message transfer techniques, including Bluetooth, Near Field Communication, SMS (short message service), enhanced SMS (EMS), multi-media message (MMS), email WAP, paging, or other known or later-developed wireless data formats.
  • SMS short message service
  • EMS enhanced SMS
  • MMS multi-media message
  • email WAP paging
  • paging or other known or later-developed wireless data formats.
  • An executable code of a computing device may be a single instruction, or many instructions, and may even be distributed over several different code segments, among different applications, and across several memory devices.
  • operational data may be identified and illustrated herein within the computing device, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices, and may exist, at least partially, as electronic signals on a system or network.
  • memory is generally a storage device of a computing device. Examples include, but are not limited to, read-only memory (ROM) and random access memory (RAM).
  • ROM read-only memory
  • RAM random access memory
  • the device or system for performing one or more operations on a memory of a computing device may be a software, hardware, firmware, or combination of these.
  • the device or the system is further intended to include or otherwise cover all software or computer programs capable of performing the various heretofore-disclosed determinations, calculations, or the like for the disclosed purposes.
  • exemplary embodiments are intended to cover all software or computer programs capable of enabling processors to implement the disclosed processes.
  • Exemplary embodiments are also intended to cover any and all currently known, related art or later developed non-transitory recording or storage mediums (such as a CD-ROM, DVD-ROM, hard drive, RAM, ROM, floppy disc, magnetic tape cassette, etc.) that record or store such software or computer programs.
  • Exemplary embodiments are further intended to cover such software, computer programs, systems and/or processes provided through any other currently known, related art, or later developed medium (such as transitory mediums, carrier waves, etc.), usable for implementing the exemplary operations disclosed below.
  • the disclosed computer programs can be executed in many exemplary ways, such as an application that is resident in the memory of a device or as a hosted application that is being executed on a server and communicating with the device application or browser via a number of standard protocols, such as TCP/IP, HTTP, XML, SOAP, REST, JSON and other sufficient protocols.
  • the disclosed computer programs can be written in exemplary programming languages that execute from memory on the device or from a hosted server, such as BASIC, COBOL, C, C++, Java, Pascal, or scripting languages such as JavaScript, Python, Ruby, PHP, Perl, or other suitable programming languages.
  • the terms“computing device” and“entities” should be broadly construed and should be understood to be interchangeable. They may include any type of computing device, for example, a server, a desktop computer, a laptop computer, a smart phone, a cell phone, a pager, a personal digital assistant (PDA, e.g., with GPRS NIC), a mobile computer with a smartphone client, or the like.
  • a server e.g., GPRS NIC
  • PDA personal digital assistant
  • a user interface is generally a system by which users interact with a computing device.
  • a user interface can include an input for allowing users to manipulate a computing device, and can include an output for allowing the system to present information and/or data, indicate the effects of the user’s manipulation, etc.
  • An example of a user interface on a computing device includes a graphical user interface (GUI) that allows users to interact with programs in more ways than typing.
  • GUI graphical user interface
  • a GUI typically can offer display objects, and visual indicators, as opposed to text-based interfaces, typed command labels or text navigation to represent information and actions available to a user.
  • an interface can be a display window or display object, which is selectable by a user of a mobile device for interaction.
  • a user interface can include an input for allowing users to manipulate a computing device, and can include an output for allowing the computing device to present information and/or data, indicate the effects of the user’s manipulation, etc.
  • An example of a user interface on a computing device includes a graphical user interface (GUI) that allows users to interact with programs or applications in more ways than typing.
  • GUI graphical user interface
  • a GUI typically can offer display objects, and visual indicators, as opposed to text-based interfaces, typed command labels or text navigation to represent information and actions available to a user.
  • a user interface can be a display window or display object, which is selectable by a user of a computing device for interaction.
  • the display object can be displayed on a display screen of a computing device and can be selected by and interacted with by a user using the user interface.
  • the display of the computing device can be a touch screen, which can display the display icon. The user can depress the area of the display screen where the display icon is displayed for selecting the display icon.
  • the user can use any other suitable user interface of a computing device, such as a keypad, to select the display icon or display object.
  • the user can use a track ball or arrow keys for moving a cursor to highlight and select the display object.
  • a computer network may be any group of computing systems, devices, or equipment that are linked together. Examples include, but are not limited to, local area networks (LANs) and wide area networks (WANs).
  • a network may be categorized based on its design model, topology, or architecture.
  • a network may be characterized as having a hierarchical internetworking model, which divides the network into three layers: access layer, distribution layer, and core layer.
  • the access layer focuses on connecting client nodes, such as workstations to the network.
  • the distribution layer manages routing, filtering, and quality-of-server (QoS) policies.
  • the core layer can provide high-speed, highly-redundant forwarding services to move packets between distribution layer devices in different regions of the network.
  • the core layer typically includes multiple routers and switches.
  • FIG. 1 illustrates a diagram of a system 100 for weapon and destructive device detection based on electromagnetic field profile in accordance with embodiments of the present disclosure.
  • the system 100 includes a computing device 102 and sensors 104 A and 104B.
  • the computing device 102 may be operably connected to sensors 104A and 104B via respective cables 106A and 106B, respectively.
  • the computing device 102 may be connected to sensors 104 A and 104B via any other suitable wired connection or wireless connection.
  • sensors 104 A and 104B are shown in the figure, it should be understood that there may be any suitable number of sensors operably connected to the computing device 102 by any suitable communication technique, and in any suitable configuration or arrangement in accordance with embodiments of the present disclosure.
  • the computing device 102 may include an input / output (EO) module 106 configured to communicatively interface with the sensors 104 A and 104B.
  • the EO module 106 may be a wire end interface or a wireless communications module for communicating with sensors 104 A and 104B.
  • the I/O module 106 may receive the electrical signals from the sensors 104A and 104B and convert the electrical signals to data for use by the computing device in accordance with embodiments of the present disclosure.
  • the sensors 104 A and 104B may each be configured to detect an electromagnetic field of nearly objects and to each output an electrical signal representative of the detected electromagnetic field.
  • the computing device 102 may be configured to receive the electrical signal(s) from each sensor 104 A and 104B, to determine whether object(s) meet a predetermined electromagnetic field profile based on the electrical signal(s), and to present a notification to a user in response to determining that an object meets the predetermined electromagnetic field profile.
  • These functionalities and other functionalities in accordance with embodiments of the present disclosure may be implemented by a security manager 108.
  • the security manager 108 may include hardware, software, firmware, or combinations thereof for implementing the functionalities described herein.
  • the security manager 108 may include memory 110 and one or more processors 112.
  • the sensors 104 A and 104B may be any suitable type of sensor for detecting a magnetic field generated by an object in proximity.
  • the sensors 104A and 104C may include induction coils.
  • the induction coils may each include either an air core or a high permeability core.
  • each induction coil may include a core made of low carbon steel, ferrite, an alloy of nickel-iron, an alloy of boron-iron-silicon, or combinations thereof.
  • the sensors 104A and 104B may comprise a pair of solenoids.
  • the sensors 104 A and 104B may be two or more sensors configured to detect magnetic flux of objects in different orientations.
  • the sensors 104A and 104B comprise a three-axis gradiometer. An output of the sensors 104A and 104B may be electrical signals representative of a detected magnetic flux.
  • FIG. 2 illustrates a flowchart of an example method for detecting weapons and destructive devices based on electromagnetic field profiles in accordance with embodiments of the present disclosure.
  • the method is described by example as being implemented by the system 100 shown in FIG. 1, although it should be appreciated that the method may be implemented by any suitable system including sensors operable to detect electromagnetic fields.
  • the method includes detecting 200 an electromagnetic field of one or more objects.
  • a person 114 may walk in proximity to the sensors 104 A and 104B and may carry objects 116 and 118.
  • the objects 116 and 118 are depicted as being carried in the person’s 114 hands.
  • the objects may be contained in a bag, briefcase, luggage, or the like carried by the person 114.
  • the object 116 is a briefcase, which is holding one or more objects.
  • the object 118 is a smartphone in this example.
  • the objects 116 and 118 may produce magnetic fields that are detectable by the sensors 104 A and 104B when the objects and sensors are in sufficiently close proximity.
  • Example objects also include, but are not limited to, weapons and destructive devices such as handguns, IEDs, rifles, knives, and the like.
  • the method of FIG. 2 includes outputting 202 an electrical signal representative of the electromagnetic field.
  • the sensors 104A and 104B can each output electrical signals that are representative of the objects 116 and 118. Further, the sensors 104 A and 104B can each output electrical signals that are representative of the magnetic fields of any objects contained in object 116 and/or other nearby objects.
  • the method of FIG. 2 includes receiving 204 the electrical signal.
  • the I/O module 106 of the computing device 102 may receive the electrical signal from each sensor 104 A and 104B and store a representation of the detected magnetic fields of objects 116 and 118 in memory 110 of the security manager 108.
  • the stored data in memory 110 may be representative of the detected magnetic fields of objects 116 and 118.
  • the method of FIG. 2 includes determining 206 whether each of the object(s) meets a predetermined electromagnetic field profile based on the electrical signal.
  • the security manager 108 may determine whether a stored magnetic field of one of the objects 116 and 118 meets a predetermined magnetic field profile.
  • the security manager 108 may store and maintain in memory 110 a library of multiple, predetermined electromagnetic field profiles.
  • the profiles may be, for example, magnetic field profiles.
  • the security manager 108 may use the profiles comparison to the signals representative of the magnetic field profiles of objects 116 and 118.
  • the profiles may be compared to the magnetic field profiles of the objects 116 and 118 to determine whether there is a match or whether there is sufficient similarity to deduce that one of the objects 116 and 118 is a weapon or destructive device or may be a weapon or destructive device.
  • the steps of detecting 200, outputting 202, receiving 204, and determining 206 can be continuously, periodically, or regularly implemented. This is so that the system 100 can continuously or regularly check as objects pass by the sensors 104 A and 104B. This can be advantageous in a secured environment or checkpoint.
  • the method of FIG. 2 includes presenting 208 a notification to a user in response to determining that object(s) meet the predetermined electromagnetic field profile.
  • the security manager 108 may control a display 120 to display a notification to a user to indicate that one of the objects 104A and 104B meets one of the stored magnetic field profiles.
  • one of the profiles may be for a handgun.
  • the display 120 may be controlled to notify a user of the match such that security action may be effected.
  • the notification may be a warning to the user.
  • any suitable user interface may be controlled for notifying a user of a match to a stored profile.
  • the system 100 shown in FIG. 1 may include conditioning circuitry 122 configured to condition electrical signals output by the sensors 104 A and 104B.
  • the conditioning circuitry 122 may condition the electrical signals such that they are suitable for receipt by the I/O module 106 of the computing device.
  • the conditioning circuitry 122 may include a frequency filter configured to entirely or at least substantially remove electrical signals from output by the sensors 104A and 104B that are outside a predetermined range of frequencies.
  • the frequency ranges filtered by the frequency filter may include frequencies outside of the expected frequency ranges of magnetic fields of objects of interest, such as weapons and destructive devices.
  • the system 100 shown in FIG. 1 may include an image capture device 124 operably connected to the computing device 102 or another electronic device.
  • the image capture device 124 may be positioned to capture images and/or video of objects (e.g ., the person 114 and objects 116 and 118) positioned in proximity to the sensors 104A and 104B. Data of the capture images and/or video may be communicated to the computing device 102 and/or another electronic device.
  • the image capture device 124 is communicatively connected to the computing device 102 such that the captured images and/or video data may be communicated to the computing device and stored in memory 110 by the security manager 108.
  • the security manager 108 may be configured to control the image capture device to capture an image and/or video of the object(s) in its field-of-view (FOV) in response to a determination that a representation of the electromagnetic field of the object(s) meets a predetermined electromagnetic field profile in accordance with embodiments disclosed herein.
  • FOV field-of-view
  • images and/or video of the objects or the scene may be captured when, for example, there is a determination that an object may be a weapon or destructive device.
  • a system may include one or more passive magnetic field measurement elements for detecting sensitive magnetic fields generated from moving and/or stationary targets.
  • the system may also implement with a suitable computing device a detection algorithm based on the classification of magnetic signatures from targets of interest used to declare an alarm when one or more of the targets are detected.
  • the system may include a gradiometer element that effectively suppresses unwanted far field signals, reducing spurious noise.
  • the system may also include a frequency filter that can effectively eliminate signals with frequencies outside of the expected band from the moving or stationary targets of interest.
  • the system may include collocated sensing elements arranged in one, two or three directions to measure one or more components of the varying magnetic field vector generated by moving targets.
  • the system may include a camera to generate an image of the entryway at the moment an alarm is generated.
  • the system may also include a user interface that allows an operator to observe an image of an entryway at a time of detection.
  • the system may also include an interconnected system that allows to transmit the alarm to one or more wired or wireless local or remote devices.
  • a system can detect weapons based on the discrimination of classified magnetic signatures from threats and background and spurious signals.
  • the system 100 shown in FIG. 1 may have this functionality.
  • a detection element or sensors
  • the reference sensitive level of the disclosed system can be the background noise at the frequency of interest.
  • the weapon magnetic signatures, the noise sources and the detection algorithms are described below.
  • the detection of threats may be based on the pre-classified or predetermined magnetic signatures (or profiles) from moving weapons such as rifles and IEDs.
  • the system may discriminate those from benign objects and from background ambient signals. Magnetic signals arise from metallic objects of interest carried by people. These include handguns and larger weapons, as well as IEDs, tools and other objects.
  • the magnetic signatures of several pistols may be classified as a marker or indicator of the signals to be detected against naturally and manmade occurring spurious signals.
  • a pistol can produce a magnetic field of approximately 280 picotesla (pT) at a range of 5 meters.
  • ferromagnetic steel components liners of the firing chamber and, sometimes, the barrel
  • a minimum signal to noise ratio of 4: 1 may be specified to provide a high probability of detection. This can motivate selection of, for example, 70 pT/Hzl/2 as an indicator of sensor noise floor target. Modeling the target or object as a magnetic dipole and calculating the multidirectional evolution of the signal as the target is carried past a sensor can enable estimation of the frequency band containing the signal.
  • bandpass filtering can be used to filter natural geomagnetic fluctuations, cultural noise, noise from sensor motion, and the like.
  • the conditioning circuitry 112 may be suitably configured with one or more filters (e.g ., a bandpass filter) to filter these noises ahead of them reaching the computing device 102.
  • Example geomagnetic fluctuations include geomagnetic pulsations (e.g., Classes Pc3, Pc4, and Pc5).
  • Example cultural noises include powerline noise, vehicle noise (e.g, automobile noise), construction activity, and the like.
  • far fields may be suppressed using an inductive sensor pair (gradiometer) in addition to profiles disclosed herein.
  • cultural noise may be suppressed with a pair of coils collecting magnetic flux with opposite currents. This can passively suppress far fields while still being effective at detecting signals that are of the order of one to a few times the separation of two“opposite” detection elements.
  • inductive coil orientation or other sensor configurations can generate noise.
  • an angular motion of 1.4 microradians in the Earth’s field (about 50 microT) can produce a transient fluctuation in the sensor’s output that is comparable in magnitude to sensor noise.
  • the disclosed sensors such as induction coils have zero sensitivity at DC, there is no change in baseline level, only a transient.
  • a bandpass filter or other suitable conditioning circuit may reduce or eliminate this sensor noise.
  • fully tracking and characterizing magnetic dipole targets or objects can require measuring six parameters as a function of time: the three components of its position vector r and the three components of its magnetic moment vector M. Determining M can be a key to characterizing and categorizing a target or object. Doing so can require a minimum of six independent measurements. In practice, multiple solutions exist when only six measurements are available, and it can take a few more to eliminate them. Measuring all three vector components of the magnetic field at one location may be inadequate to specify dipole magnitude and location.
  • Measuring the gradient tensor at two locations, or measuring the field and gradient at a single location, can suffice to locate and characterize the target unambiguously.
  • a magnetic measure that provides an unambiguous, monotonic closer-farther signal is the scalar magnitude of the gradient tensor (the Pythagorean sum of all nine components).
  • a single or a set of magnetic flux sensing elements is sufficient for the threat detection modality.
  • a second consideration in target detection is that, since the signal is not a repeating one, techniques like signal averaging to improve signal to noise ratio (SNR) are not easily usable.
  • SNR signal to noise ratio
  • FIG. 3 is a graph showing a signal of a test magnet being rotated end-over-end to produce an oscillating signal at a distance of 9.2 m from two induction-coil sensors, along with the residual obtained by least squares subtraction of one sensor output from the other.
  • the quasi-periodic signal may be detected with a signal-to-noise ratio (SNR) of somewhat less than 2.
  • FIG. 4 is a graph that shows the signal from the same magnet being carried twice past the sensors at a brisk walking pace, with the distance at closest approach being 4.7 m.
  • the target signal is detected with an SNR of approximately 2, despite the much smaller range to the target that can yield substantially higher SNR.
  • a suitable signal conditioning technique implemented by the conditioning circuitry 122 shown in FIG. 1 can allow for increased detection performance.
  • a magnetic flux detection element is oriented along the x-axis of a coordinate system whose other horizontal axis is y, with z being vertical.
  • the sensor’s output is band-pass filtered in the anticipated signal band of interest.
  • the sensor output taken over a sliding window of a length of time is subsequently passed through a detector to determine if there is a potential signal of interest. In some embodiments, this may include image processing for motion detection to reduce false alarm from environmental noise.
  • One or more sensor outputs from sensors 104 A and 104B taken over a sliding window of a length in time may subsequently be evaluated by the security manager 108 using machine classification algorithms, such as but not limited to, linear regression, logistics regression, Naive Bayes, k-means, k-nearest neighbor, support vector machines, neural networks, or the like.
  • machine classification algorithms such as but not limited to, linear regression, logistics regression, Naive Bayes, k-means, k-nearest neighbor, support vector machines, neural networks, or the like.
  • These comparative classifier values may be generated by the security manager 108 using any one of several machine learning techniques with data taken with threat devices (e.g ., guns, knives, improvised explosives, etc.), as well as clear signals and distractors, such as common clutter (cell phones, keys, coins, wallets, purses, tablets, laptops, musical instruments, luggage, strollers, etc.).
  • the output of the classification algorithms can come in several forms, including, but not limited to, identification of
  • a multi-directional sensor may be configured in a way that various magnetic moment components are detected. This enables an estimate of the target’s magnetic moment. Having approximately constrained the object’s moment and direction, the characteristic frequency can provide an approximate measure of the target’s speed. Having the peak magnitude information can refine the processing by providing a field profile that can, for instance, help distinguish between a single dipole-like target and a collection of many dipoles ( e.g ., a group of people each carrying handguns).
  • the result of the classification algorithm may subsequently trigger an alarm or alert to be sent to an operator.
  • notification or instruction to trigger the alarm can be communicated over a network connection and includes an alert image.
  • alarms are noted, along with the time stamp for the event, and are further processed for potential threats.
  • an induction coil may be used as a sensor to measure the magnetic flux generated by a moving target of interest.
  • the induction coil can have an air core or a high permeability core.
  • a high permeability air core solenoid may be used.
  • the material for the core may be for example low carbon steel, ferrite, or alloys of nickel-iron or boron-iron-silicon.
  • FIGs. 5A and 5B illustrate a side perspective view and a side view, respectively, of an example solenoid coil with a high permeability core that may be used as a sensor in accordance with embodiments of the presently disclosed subject matter.
  • this solenoid coil may be used as one or both of the sensors 104A and 104B shown in FIG. 1.
  • this configuration achieves the sensitivity of the ambient noise or better in the frequency range of interest.
  • Other sensing technologies may be utilized. For example but not limited to. fluxgate magnetometer devices.
  • the sensors disclosed herein may operate at low frequencies. Therefore, the signals are not attenuated by walls or metallic sheets.
  • the sensors may therefore be covert (e.g., placed inside metallic or non-metallic enclosures or even hidden behind walls).
  • FIGs. 6-10 illustrate different views of example configurations of weapon and destructive device detection system in accordance with embodiments of the present disclosure.
  • the figure shows a view of sensors A and B positioned at sides of an entryway.
  • the sensors A and B are solenoids.
  • the sensors A and B can detect the flux generated by objects moving in their proximity.
  • a person walking in between the sensors A and B with a weapon can result in detectable signals in one or both of the sensors A and B.
  • FIG. 7 shows two sensor pairs A and B with coils in each pair in opposite orientations (gradiometer). Each pair A and B is positioned at each side of an entryway.
  • far field signals may be suppressed by using such a pair of identical sensors collecting magnetic flux in opposite orientations.
  • the signals may be suppressed by connecting the opposite solenoids in series or by subtracting the signals collected from the two individual sensors. Signals generated at distances significantly larger than the separation of the sensors are passively and effectively suppressed. While signals in the proximity of the sensor pair are detectable, changing the separation of the sensors allows to control the sensitivity area and the degree of far field suppression.
  • FIG. 8 shows a set of three collocated induction coils placed along the three Cartesian axes ⁇ i.e. , axes x, y, and z).
  • the multiple orientations may be used to collect components of the magnetic field flux as objects are moved in the proximity of the sensor.
  • the signals can be exploited by the classification detection algorithms for matching to a profile to increase specificity and therefore provide high detection performance.
  • FIG. 9 shows a three-axis gradiometer.
  • each of the three collocated pairs of opposite induction coils are oriented along the Cartesian axes (i.e., axes x, y, and z).
  • FIG. 10 shows an example distribution of pairs of coils forming a three- axis gradiometer.
  • This sensor may, for example, be placed inside a detector box - covert or not covert.
  • FIG. 11 illustrates a diagram of an example configuration for entryway security in accordance with embodiments of the present disclosure.
  • each of the boxes may contain a unidirectional or multi-directional sensor A and B.
  • the boxes are placed on the sides of the entryway.
  • a camera can be positioned as indicated and directed to the sensitive area of the sensors A and B.
  • an alarm may be generated, together with a time stamp and an image. The image can help with security measures following an alarm, showing the entryway at the instant in which the alarm was generated.
  • the term logical circuit or component might describe a given unit of functionality that can be performed in accordance with one or more embodiments of the technology disclosed herein.
  • a component might be implemented utilizing any form of hardware, software, or a combination thereof.
  • processors, controllers, ASICs, PLAs, PALs, CPLDs, FPGAs, logical components, software routines or other mechanisms might be implemented to make up a component or logical circuit.
  • the various components or logical circuits described herein might be implemented as discrete components or the functions and features described can be shared in part or in total among one or more components or logical circuits - as represented in FIG.
  • FIG. 12 illustrates a block diagram of an example system 1300 for implementing functionality described herein.
  • the various features and functionality described herein may be implemented in any given application and can be implemented in one or more separate or shared components in various combinations and permutations.
  • the term logical circuit may describe a collection of components configured to perform one or more specific tasks. Even though various features or elements of functionality may be individually described or claimed as separate components or logical circuits, one of ordinary skill in the art will understand that these features and functionality can be shared among one or more common software and hardware elements, and such description shall not require or imply that separate hardware or software components are used to implement such features or functionality.
  • the system 1300 may represent, for example, computing or processing capabilities found within desktop, laptop and notebook computers; hand-held computing devices (PDA’s, smart phones, cell phones, palmtops, etc.), ⁇ mainframes, supercomputers, workstations or servers; or any other type of special purpose or general-purpose computing devices as may be desirable or appropriate for a given application or environment.
  • PDA hand-held computing devices
  • mainframes mainframes
  • supercomputers workstations or servers
  • workstations or servers or any other type of special purpose or general-purpose computing devices as may be desirable or appropriate for a given application or environment.
  • System 1300 might also represent computing capabilities embedded within or otherwise available to a given device.
  • a computing component might be found in other electronic devices such as, for example, digital cameras, navigation systems, cellular telephones, portable computing devices, modems, routers, WAPs, terminals and other electronic devices that might include some form of processing capability.
  • System 1300 might include, for example, one or more processors, controllers, control components, or other processing devices, such as a processor 1304.
  • Processor 1304 may be implemented using a general-purpose or special-purpose processing logical circuits such as, for example, a microprocessor, controller, or other control logic.
  • processor 1304 is connected to a bus 1302, although any communication medium can be used to facilitate interaction with other components of computing component 1300 or to communicate externally.
  • the system 1300 may also include one or more memory components, simply referred to herein as main memory 1308.
  • main memory 1308 random access memory (RAM) or other dynamic memory may be used for storing information and instructions to be executed by processor 1304.
  • Main memory 1308 might also be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor 1304.
  • Computing component 1300 might likewise include a read only memory (“ROM”) or other static storage device coupled to bus 1302 for storing static information and instructions for processor 1304.
  • ROM read only memory
  • the system 1300 might also include one or various forms of information storage devices 1310, which might include, for example, a media drive 1312 and a storage unit interface 1320.
  • the media drive 1312 might include a drive or other mechanism to support fixed or removable storage media 1314.
  • a hard disk drive, an optical disk drive, a CD or DVD drive (R or RW), or other removable or fixed media drive might be provided.
  • storage media 1314 might include, for example, a hard disk, an optical disk, a CD or DVD, or other fixed or removable medium that is read by, written to or accessed by media drive 1312.
  • the storage media 1314 can include a computer usable storage medium having stored therein computer software or data.
  • information storage mechanism might include other similar instrumentalities for allowing computer programs or other instructions or data to be loaded into the system 1300.
  • Such instrumentalities might include, for example, a fixed or removable storage unit 1322 and an interface 1320.
  • Examples of such storage units 1322 and interfaces 1320 can include a program cartridge and cartridge interface, a removable memory (for example, a flash memory or other removable memory component) and memory slot, a PCMCIA slot and card, and other fixed or removable storage units 1322 and interfaces 1320 that allow software and data to be transferred from the storage unit 722 to the system 1300.
  • the system 1300 may also include a communications interface 1324.
  • Communications interface 1324 might be used to allow software and data to be transferred between computing component 1300 and external devices.
  • Examples of communications interface 1324 might include a modem or softmodem, a network interface (such as an Ethernet, network interface card, WiMedia, IEEE 802. XX, or other interface), a communications port (such as for example, a USB port, IR port, RS232 port, Bluetooth® interface, or other port), or other communications interface.
  • Software and data transferred via communications interface 1324 might typically be carried on signals, which can be electronic, electromagnetic (which includes optical) or other signals capable of being exchanged by a given communications interface 1324. These signals might be provided to communications interface 1324 via a channel 1328.
  • This channel 1328 might carry signals and might be implemented using a wired or wireless communication medium.
  • Some examples of a channel might include a phone line, a cellular link, an RF link, an optical link, a network interface, a local or wide area network, and other wired or wireless communications channels.
  • computer program medium and “computer usable medium” are used to generally refer to media such as, for example, memory 1308, storage unit 1320, media 1314, and channel 1328. These and other various forms of computer program media or computer usable media may be involved in carrying one or more sequences of one or more instructions to a processing device for execution. Such instructions embodied on the medium, are generally referred to as“computer program code” or a“computer program product” (which may be grouped in the form of computer programs or other groupings). When executed, such instructions might enable the system 1300 to perform features or functions of the disclosed technology as discussed herein.

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Abstract

L'invention concerne des systèmes et des procédés de détection d'armes et de dispositifs destructifs sur la base d'un profil de champ électromagnétique. Selon un aspect, un système comprend un ou plusieurs capteur(s) configuré(s) pour détecter un champ électromagnétique d'un ou de plusieurs objet(s) et pour émettre un signal électrique représentatif du champ électromagnétique. Le système comprend également un dispositif informatique connecté fonctionnellement au(x) dit(s) un ou plusieurs capteur(s). En outre, le dispositif informatique est configuré pour recevoir le signal électrique. Le dispositif informatique est également configuré pour déterminer si chaque objet ou chacun desdits objets satisfait un profil de champ électromagnétique prédéterminé sur la base du signal électrique. En outre, le dispositif informatique est configuré pour présenter une notification à un utilisateur en réponse à la détermination qu'un parmi les objets correspond au profil de champ électromagnétique prédéterminé.
PCT/US2020/015136 2019-01-27 2020-01-27 Systèmes et procédés de détection d'armes et de dispositifs destructifs sur la base d'un profil de champ électromagnétique WO2020209923A2 (fr)

Priority Applications (8)

Application Number Priority Date Filing Date Title
MX2021009010A MX2021009010A (es) 2019-01-27 2020-01-27 Sistemas y métodos de detección de arma y dispositivo destructivo basado en perfil de campo electromagnético.
BR112021014687-3A BR112021014687A2 (pt) 2019-01-27 2020-01-27 Sistemas e métodos para detecção de armas e dispositivos destrutivos com base em perfil de campo eletromagnético
AU2020271483A AU2020271483A1 (en) 2019-01-27 2020-01-27 Systems and methods for weapon and destructive device detection based on electromagnetic field profile
US17/419,334 US20220082721A1 (en) 2019-01-27 2020-01-27 Systems and methods for weapon and destructive device detection based on electromagnetic field profile
CA3127933A CA3127933A1 (fr) 2019-01-27 2020-01-27 Systemes et procedes de detection d'armes et de dispositifs destructifs sur la base d'un profil de champ electromagnetique
EP20788418.0A EP3914940A2 (fr) 2019-01-27 2020-01-27 Systèmes et procédés de détection d'armes et de dispositifs destructifs sur la base d'un profil de champ électromagnétique
GB2112194.2A GB2595192A (en) 2019-01-27 2020-01-27 Systems and methods for weapon and destructive device detection based on electromagnetic field profile
CONC2021/0011317A CO2021011317A2 (es) 2019-01-27 2021-08-27 Sistemas y métodos de detección de armas y dispositivos destructivos basados en perfil de campo electromagnético

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US201962797341P 2019-01-27 2019-01-27
US62/797,341 2019-01-27

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CA (1) CA3127933A1 (fr)
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EP3914940A2 (fr) 2021-12-01
MX2021009010A (es) 2022-01-19
CA3127933A1 (fr) 2020-10-15
BR112021014687A2 (pt) 2021-09-28
US20220082721A1 (en) 2022-03-17
GB202112194D0 (en) 2021-10-06

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